{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This allows multiple outputs from a single jupyter notebook cell:\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x575 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %load scratch_pad/issues/so65487952_ans.py\n",
    "import mplfinance as mpf\n",
    "import yfinance as yf\n",
    "import pandas as pd\n",
    "import datetime as dt\n",
    "from pandas_datareader import data as pdr \n",
    "\n",
    "yf.pdr_override()\n",
    "start = dt.datetime.now() - dt.timedelta(60)\n",
    "now = dt.datetime.now()\n",
    "\n",
    "stock = \"AMZN\"\n",
    "filename = stock.lower()+'.png'\n",
    "\n",
    "df = pdr.get_data_yahoo(stock ,start , now)\n",
    "mpf.plot(df,type='candle',style='yahoo')#,savefig='amzn.png')\n",
    "mpf.plot(df,type='candle',style='yahoo',savefig=filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r-- 1 dino dino 1488085 Dec 27 15:56 addplot.ipynb\r\n",
      "-rw-r--r-- 1 dino dino   22140 Dec 30 19:15 \u001b[0m\u001b[01;35mamzn.png\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "ls -l a*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cp amzn.png /mnt/c/users/dgold/Desktop/."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x575 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import mplfinance as mpf\n",
    "import yfinance as yf\n",
    "import pandas as pd\n",
    "import datetime as dt\n",
    "from pandas_datareader import data as pdr \n",
    "\n",
    "yf.pdr_override()\n",
    "now = dt.datetime.now()\n",
    "start = now - dt.timedelta(60)\n",
    "\n",
    "\n",
    "stock = \"AMZN\"\n",
    "filename = stock.lower()+'.png'\n",
    "\n",
    "df = pdr.get_data_yahoo(stock ,start , now)\n",
    "mpf.plot(df,type='candle',style='yahoo',savefig=filename)\n",
    "mpf.plot(df,type='candle',style='yahoo')#,savefig=filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert yahoo finance data to readable to mplfinance\n",
    "#df.index = pd.to_datetime(df.index)\n",
    "#dvalues = df[['Open','High', 'Low','Close']].values.tolist()\n",
    "\n",
    "#pdates = mdates.date2num(df.index)\n",
    "#ohlc = [ [pdates[i]] + dvalues[i] for i in range(len(pdates)) ]\n",
    "\n",
    "#plt.style.use('fivethirtyeight')\n",
    "#fig, ax = plt.subplots(figsize = (16,12))\n",
    "\n",
    "#candlestick_ohlc(ax, ohlc, width=0.4, colorup='green', colordown='red') # i want to save this chart. \n",
    "#plt.savefig('amzn.png') # i have tried this but not avail\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
